MATEC Web Conf.
Volume 296, 20192019 7th International Conference on Traffic and Logistic Engineering (ICTLE 2019)
|Number of page(s)||5|
|Published online||22 October 2019|
- XU Yanmin, Tang Chengang. Identifying gloomy spots of ship collision accident with grid theory [J]. Navigation of China, 2013, 36(4):72-75. [Google Scholar]
- DU Shanshan, CHEN Houzhong Identification of waterway traffic black-spot [J] Journal of Dalian Maritime University, 2016, 42(2):46-5. [Google Scholar]
- BAO Haitao. Evaluation of accident black spots on roads using clustering algorithm [D]. Changchun: Jilin University, 2005. [Google Scholar]
- Zhang Man. Research on clustering and classification algorithm based on rough set and inclusion degree [D]. Qingdao: Qingdao Technological University, 2015. [Google Scholar]
- Michal B, Richard A, ZBYNEK J. Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation [J]. Elsevier, 2013, 55(3) :265. [Google Scholar]
- Saccomanno F, Grossir, GRECO D, et al. Identifying blackspots along highway SS107 in southern Italy using two models [J]. Journal of Transportation Engineering. 2001, 127(6) : 515-522. [CrossRef] [Google Scholar]
- Dunn J C. A fuzzy relative of the ISODATA process its use in delecting compact well-separated clusters [J]. Journal of Cybenetics, 1974, 3(3) : 32-57. [CrossRef] [Google Scholar]
- Xiao Shen, GUO Xiucheng, XU Jiandong. Application fuzzy clustering method in the highway traffic black-spot cause of formation analysis [J]. Journal of Transportation Systems Engineering and Information Technology, 2002, 2(3) : 40-43. [Google Scholar]
- Wang Hai. Based on spatial analysis technology of traffic accident black point identification and cause analysis [D]. Beijing: Tsinghua University, 2014. [Google Scholar]
- Sandhu H A, Singh G, SISODIA M S, et al. Identification of black spots on highway with kernel density estimation method [J]. Journal of the Indian Society of Remote Sensing, 2016, 44 (3) :457-464. [CrossRef] [Google Scholar]
- Geurts K, Wets G, BRIJS T, et al. Identification and ranking of black spots: sensitivity analysis [J]. Transportation Research Record Journal of the Transportation Research Board, 2004, 1897(1) : 34-42. [CrossRef] [Google Scholar]
- Andreas G, Kyriacos C M. Black spots identification through a Bayesian networks quantification of accident risk index [J]. Elsevier, 2013, 28(3) : 28-43. [Google Scholar]
- Jiang Hua, Li Jing, Yi Shenghe, et al. A new hybrid meth—od based onpartitioning—based DBSCAN and antclustering[J] Expen Systems with Applications, 2011, 38(8):9373-9381. [CrossRef] [Google Scholar]
- Hong FangZhou,Peng Wang. DBSCAN algorithm for parameter adaptive determination method [J]. Journal of xi ‘an university of technology,2012,28(3):289-292. DOI:10.3969/j.issn.1006-4710.2012.03.007. [Google Scholar]
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